Please use this identifier to cite or link to this item:
https://ir.swu.ac.th/jspui/handle/123456789/12897
Title: | Learning outcomes evaluation based on mixed diagnostic tests and cognitive graphic tools |
Authors: | Yankovskaya A.E. Dementev Y.N. Lyapunov D.Y. Yamshanov A.V. |
Keywords: | Computer circuits Computer testing Fuzzy logic Intelligent systems Learning systems Linguistics Pattern recognition Pattern recognition systems Students Threshold logic Trajectories Cognitive graphic tools Computer-based testing Effective learning Intelligent learning Knowledge evaluations Learning trajectories Mixed diagnostic tests N simplex Education |
Issue Date: | 2018 |
Abstract: | In this paper, we discuss the relevance of students’ learning outcomes evaluation using computer-based testing. The learning process is based on mixed diagnostic tests. For the purpose of evaluation, we use the threshold, fuzzy logic and cognitive graphic tools. The construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students’ knowledge evaluation is proposed for a number of disciplines. We suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects for effective learning. The developed approach is used for a number of both the humanities and technical disciplines. One of useful outcomes of mixed diagnostic tests application is the learning trajectory design for each individual. We construct students’ learning trajectory using the intelligent learning and testing system and suggest defining their inherent approach to the learning process within the problem area. © 2018, Springer International Publishing AG. |
URI: | https://ir.swu.ac.th/jspui/handle/123456789/12897 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030631624&doi=10.1007%2f978-3-319-67843-6_11&partnerID=40&md5=14a2f5c7608ceed588ef31a894df5943 |
ISSN: | 21945357 |
Appears in Collections: | Scopus 1983-2021 |
Files in This Item:
There are no files associated with this item.
Items in SWU repository are protected by copyright, with all rights reserved, unless otherwise indicated.